Local and global features of genetic networks supporting a phenotypic switch

被引:2
|
作者
Shomar, Aseel [1 ,2 ]
Barak, Omri [2 ,3 ]
Brenner, Naama [1 ,2 ]
机构
[1] Technion, Dept Chem Engn, Haifa, Israel
[2] Technion, Lorry Lokey Ctr Life Sci & Engn, Network Biol Res Labs, Haifa, Israel
[3] Technion, Rappaport Fac Med, Haifa, Israel
来源
PLOS ONE | 2020年 / 15卷 / 09期
关键词
EPITHELIAL-MESENCHYMAL TRANSITION; NEGATIVE FEEDBACK LOOP; BOOLEAN NETWORK; PLASTICITY; MODELS; ZEB1;
D O I
10.1371/journal.pone.0238433
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Phenotypic switches are associated with alterations in the cell's gene expression profile and are vital to many aspects of biology. Previous studies have identified local motifs of the genetic regulatory network that could underlie such switches. Recent advancements allowed the study of networks at the global, many-gene, level; however, the relationship between the local and global scales in giving rise to phenotypic switches remains elusive. In this work, we studied the epithelial-mesenchymal transition (EMT) using a gene regulatory network model. This model supports two clusters of stable steady-states identified with the epithelial and mesenchymal phenotypes, and a range of intermediate less stable hybrid states, whose importance in cancer has been recently highlighted. Using an array of network perturbations and quantifying the resulting landscape, we investigated how features of the network at different levels give rise to these landscape properties. We found that local connectivity patterns affect the landscape in a mostly incremental manner; in particular, a specific previously identified double-negative feedback motif is not required when embedded in the full network, because the landscape is maintained at a global level. Nevertheless, despite the distributed nature of the switch, it is possible to find combinations of a few local changes that disrupt it. At the level of network architecture, we identified a crucial role for peripheral genes that act as incoming signals to the network in creating clusters of states. Such incoming signals are a signature of modularity and are expected to appear also in other biological networks. Hybrid states between epithelial and mesenchymal arise in the model due to barriers in the interaction between genes, causing hysteresis at all connections. Our results suggest emergent switches can neither be pinpointed to local motifs, nor do they arise as typical properties of random network ensembles. Rather, they arise through an interplay between the nature of local interactions, and the core-periphery structure induced by the modularity of the cell.
引用
收藏
页数:19
相关论文
共 50 条
  • [41] Evolution of local and global monopole networks
    Martins, C. J. A. P.
    Achucarro, A.
    [J]. PHYSICAL REVIEW D, 2008, 78 (08):
  • [42] SPECIAL REPORT ON LOCAL AND GLOBAL NETWORKS
    MOKHOFF, N
    [J]. COMPUTER DESIGN, 1985, 24 (11): : 49 - 49
  • [43] Comparison of Local and Global Ranking in Networks
    Zehnalova, Sarka
    Kudelka, Milos
    Horak, Zdenek
    Kroemer, Pavel
    Snasel, Vaclav
    [J]. PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INNOVATIONS IN BIO-INSPIRED COMPUTING AND APPLICATIONS (IBICA 2014), 2014, 303 : 355 - 364
  • [44] Stochastic models for regulatory networks of the genetic toggle switch
    Tian, Tianhai
    Burrage, Kevin
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2006, 103 (22) : 8372 - 8377
  • [45] INTEGRATION OF LOCAL AND GLOBAL FEATURES FOR FACE RECOGNITION
    Chen, Cun-Jian
    [J]. 2008 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND SIGNAL PROCESSING, VOLS 1 AND 2, 2007, : 193 - 198
  • [46] Mackerel Classification using Global and Local Features
    Nagaoka, Yoshito
    Miyazaki, Tomo
    Sugaya, Yoshihiro
    Omachi, Shinichiro
    [J]. 2018 IEEE 23RD INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2018, : 1209 - 1212
  • [47] Local and global Gabor features for object recognition
    Kamarainen J.-K.
    Kyrki V.
    Kälviäinen H.
    [J]. Pattern Recognition and Image Analysis, 2007, 17 (01) : 93 - 105
  • [48] On the analysis of local and global features for hyperemia grading
    Sanchez, L.
    Barreira, N.
    Sanchez, N.
    Mosquera, A.
    Pena-Verdeal, H.
    Yebra-Pimentel, E.
    [J]. NINTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2016), 2017, 10341
  • [49] CHIMPANZEE IDENTIFICATION USING GLOBAL AND LOCAL FEATURES
    Loos, Alexander
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2013, : 2347 - 2351
  • [50] Object Representation Fusing Global and Local Features
    Li, Tianwen
    Gao, Yun
    [J]. MECHATRONICS, ROBOTICS AND AUTOMATION, PTS 1-3, 2013, 373-375 : 1022 - 1026